개선된 유전해법을 이용한 비선형 최적화 모델 = Nonlinear Optimization Models using Improved Genetic Algorithms

다국어 초록 (Multilingual Abstract)

The optimization problem is to select the best of many possible design alternatives in a complex design space.
Genetic algorithms, one of numerous techniques to search optimal solution, have been sucessfully applied to various problems (for example, parameter tuning in expert systems, structural systems with a mix of continuous, integer and discrete design variables) that could not have been readily solved with more conventional computational technique. But, conventional genetic algorithms are ill defined for two classes of problems ie. parameter convergence and penalty function.
Therefore, this paper develops improved genetic algorithms to solve these problems. As a case study, numerical examples are demonstrated to show the effectiveness of the improved genetic algorithms.

목차 (Table of Contents)

• 목차
• ABSTRACT
• 1. 서론
• 2. 유전 알고리즘
• 3. 기존의 유전 알고리즘의 문제점과 개선된 유전알고리즘 (IGA)의 설계
• 4. 사례연구
• 5. 결론
• 참고문헌